Optimizing Edge-Cloud Synergy for Big Data Analytics

Raghubir Singh, Neeraj Kumar

Research output: Contribution to conferencePaperpeer-review


High-computational complexity tasks benefit greatly in time requirements by offloading from edge nodes to cloud resources. In contrast, low-complexity tasks exhibit little competitive advantage from this edge-cloud synergy. By reformatting the offloading process to partition low-complexity Big Data tasks between one edge but multiple cloud centres up to 80% of the tasks can be served by cloud resources with major reductions in total task completion times; this is favoured by accessing 5G speeds in the Wireless Local Area Network to leverage the greater processing speeds of cloud resources. High-complexity tasks also are agnostic to queuing delays in cloud resources but low-complexity tasks are less robust and require the edge-cloud orchestration software embedded in edge nodes to be able to divert such tasks to optimal choices of cloud destinations with full awareness of Wide Area Network speeds, cloud processing advantages and minimal queueing options
Original languageEnglish
Number of pages6
Publication statusPublished - 18 Apr 2023
Event2023 IEEE 13th Annual Computing and Communication Workshop and Conference (CCWC) -
Duration: 8 Mar 2023 → …


Conference2023 IEEE 13th Annual Computing and Communication Workshop and Conference (CCWC)
Period8/03/23 → …
Internet address


  • Application-level orchestration
  • Computational complexity
  • Edge-Cloud synergy
  • WAN
  • WLAN

ASJC Scopus subject areas

  • Information Systems and Management
  • Artificial Intelligence
  • Control and Optimization
  • Instrumentation
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications
  • Computer Science Applications


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